Detecting balanced translocations using tissue sections plays an important diagnostic role in cases of hematological malignancies. Manual scoring is often problematic due to truncation and overlapping of nuclei. Reports have described automated analysis using primarily tile sampling. The aim of this study was to investigate an automated fluorescent in situ hybridization analysis method using grid sampling on tissue sections, and compare the performance of dual-fusion (DF) and break-apart (BA) probes in this setting. Ten follicular, 10 mantle cell lymphoma, and 10 translocation-negative samples were used to set the threshold of false positivity using IGH/CCND1, IGH/BCL-2 DF, and IGH BA probes. The cut-off distances of red and green signals to define fusion signals were 0.5, 1.0, and 1.2 mum for the IGH/CCND1, IGH/BCL-2 DF, and IGH BA probes, respectively. The mean false positivity of grid units was 5.3, 11.4, and 28.1%, respectively. Ten to 14 additional samples analyzed blindly and were correctly classified using each probe. Discriminating positive and negative samples using automated analysis and grid sampling was possible with each probe, although different definitions of fusion signals were required due to the different physical distances between the DNA probes. Using the DF probes resulted in lower false positivity, which was less affected by signal numbers per grid units.

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